Automated Planning

Theory and Practice
Erscheinungsjahr 2004
ISBN: 978-1-55860-856-6
Verlag: Elsevier Science

Buch, Englisch, 672 Seiten, Format (B × H): 196 mm x 241 mm, Gewicht: 1529 g

Automated planning technology now plays a significant role in a variety of demanding applications, ranging from controlling space vehicles and robots to playing the game of bridge. These real-world applications create new opportunities for synergy between theory and practice: observing what works well in practice leads to better theories of planning, and better theories lead to better performance of practical applications.

Automated Planning mirrors this dialogue by offering a comprehensive, up-to-date resource on both the theory and practice of automated planning. The book goes well beyond classical planning, to include temporal planning, resource scheduling, planning under uncertainty, and modern techniques for plan generation, such as task decomposition, propositional satisfiability, constraint satisfaction, and model checking.

The authors combine over 30 years experience in planning research and development to offer an invaluable text to researchers, professionals, and graduate students.

Zielgruppe

Primary audience: Senior undergraduate and graduate students in AI, Robotics, and Operations Research (in CS, EE and CompEng departments, mainly)

Secondary audience: Researchers and practitioners in artificial intelligence, robotics, and operations research

Autoren/Hrsg.

Ghallab, Malik

Nau, Dana

Traverso, Paolo

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik

Inhaltsverzeichnis

1 Introduction and Overview

I Classical Planning 2 Representations for Classical Planning3 Complexity of Classical Planning4 State-Space Planning5 Plan-Space Planning II Neoclassical Planning 6 Planning-Graph Techniques7 Propositional Satisfiability Techniques8 Constraint Satisfaction Techniques

III Heuristics and Control Strategies 9 Heuristics in Planning10 Control Rules in Planning11 Hierarchical Task Network Planning12 Control Strategies in Deductive Planning IV Planning with Time and Resources 13 Time for Planning14 Temporal Planning15 Planning and Resource Scheduling

V Planning under Uncertainty 16 Planning based on Markov Decision Processes17 Planning based on Model Checking18 Uncertainty with Neo-Classical Techniques

VI Case Studies and Applications 19 Space Applications20 Planning in Robotics21 Planning for Manufacturability Analysis22 Emergency Evacuation Planning 23 Planning in the Game of Bridge

VII Conclusion 24 Conclusion and Other Topics

VIII Appendices A Search Procedures and Computational ComplexityB First Order LogicC Model Checking

Über Autor(innen)

Traverso, Paolo
Paolo Traverso is the Head of Sistemi di Ragionamento Automatico at the Instituto Trentino di Cultura - Instituto per la Ricerca Scientifica e Tecnologica, (ITC-IRST). He was the project leader of industrial and experimental projects such as the development of Rail Traffic Management Systems, the design of tools for Automatic Train Protection, the synthesis of industrial controllers, and the development of systems for planning and control in space environment.

Ghallab, Malik
Malik Ghallab is Director of Research at the Laboratoire d'Analyse et d'Architecture des Systèmes, Centre National de la Recherche Scientifique, LAAS-CNRS, Toulouse. He was the director of the French national AI program, coordinated the five national research programs in information science, and served as the chair of ASTI, the French technical society in information sciences and technologies. Currently, he is also the director of the French national interdisciplinary program on robotics and artificial entities (Robea).